Electrophysiology measurement and training and remote databased and data analysis measurement method and system

ABSTRACT

A method and system provides for electrophysiological data analysis in a networked processing environment. The method and system includes receiving, via a networked connection, electrophysiological data of a patient and electronically performing, via at least one network processing device, a data analysis on the electrophysiological data. The method and system includes generating at least one report based on the data analysis, wherein the at least one report includes determination of one or more intervention options for the patient and therein transmitting the report to a recipient device across the network connection for utilization with the patient. The results of the report direct the user to apply from within the same system non-invasive brain stimulation, neurofeedback, and biofeedback modalities. Re-assessment can occur from within the same system following the training or modulation of electrophysiology and thereby generate a comparison report showing functional changes from the provided intervention or combined interventions.

PRIORITY CLAIMS

The present Application is a Continuation of and claims priority to U.S.patent application Ser. No. 14/856,209 filed Sep. 16, 2015, issued asU.S. Pat. No. 9,629,568, which is a continuation of and claims priorityto U.S. patent application Ser. No. 14/215,431 filed Mar. 17, 2014,issued as U.S. Pat. No. 9,165,492, which is a continuation-in-part ofand claims priority to U.S. patent application Ser. No. 13/742,066 filedJan. 15, 2013, issued as U.S. Pat. No. 8,838,247, which is acontinuation of and claims priority to U.S. patent application Ser. No.13/543,204, filed Jul. 6, 2012, issued as U.S. Pat. No. 8,380,316, whichis a continuation of and claims priority to U.S. patent application Ser.No. 12/979,419, filed Dec. 28, 2010, issued as U.S. Pat. No. 8,239,030,which is based on and claims priority to U.S. Provisional PatentApplication Ser. No. 61/292,791 filed Jan. 6, 2010.

The present application is a Continuation of and claims priority to U.S.patent application Ser. No. 14/856,209 filed Sep. 16, 2015, which is acontinuation of and claims priority to U.S. patent application Ser. No.14/215,431 filed Mar. 17, 2014, issued as U.S. Pat. No. 9,165,492, whichfurther claims priority to U.S. Provisional Patent Application Ser. No.61/791,649 filed Mar. 15, 2013.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains material,which is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever.

FIELD OF INVENTION

The disclosed technology relates generally to the assessment andremediation of abnormal brain and physiological functioning. Morespecifically, the technology relates to detection, assembling andmanagement of data acquired based on the performance ofelectrophysiology testing.

BACKGROUND

Traumatic brain injuries can result in physical and/or emotionaldysfunction. Post traumatic stress disorder (PTSD) symptoms are similarto those of a mild traumatic brain injury (mTBI) and the two aredifficult to differentiate using current assessment methodologies suchas symptom assessments and questionnaires. In Army deployment,statistics have shown that upwards of 20% of soldiers suffer from mildtraumatic brain injury (mTBI). Head and neck injuries, including severebrain trauma, have been reported in one quarter of United States servicemembers who have been evacuated from Iraq and Afghanistan in the firstdecade of the 21st century. A common cause of such injuries arises fromexposure to percussive force from explosive devices. Further, recentmilitary analysis indicates that over 90% of patients with acute mTBIwill have vestibular (inner ear balance) disorders and those vestibulardisorders are present in over 80% of persons with chronic mTBI symptoms.Likewise, stress disorders further affect numerous individuals, whetherin a military or civilian situation. Brain injuries may further beincurred from car and bicycle accidents, sports accidents, falls, andthe like. Up to 15% of persons suffering even a mild brain injury, orconcussion, will suffer from persistent symptoms for more than a year,which significantly negatively affect their ability to work and functionin daily life. It is estimated that there are currently 5.3 millionAmericans living with a disability as a result of a TBI. There areapproximately 1.5 million diagnosed brain injuries in the U.S. annually,and it is estimated that another 2 million TBIs occur but are notproperly diagnosed. Current assessment methods are either prohibitivelyexpensive or do not diagnose the root cause of the suffering. Thus,there is a need in the art to accurately and quickly assess brain injuryand associated dysfunction and then find ways to aid or enhance optimalfunctioning.

The brain is composed of about 100 billion neurons, more than 100billion support cells and between 100 and 500 trillion neuralconnections. Each neuron, support cell and neural connection isextremely delicate, and the neural connections are tiny (approximately 1micrometer). When the brain moves within the skull, such as occurs inrapid acceleration/deceleration (e.g., exposure to sudden impact and/orexplosive devices), axons within the brain can pull, stretch and tear.If there is sufficient injury to the axon or support cells, the cellwill die, either immediately or within a few days. Such damage can occurnot only in the region that suffered direct trauma but in multipleregions (e.g., diffuse axonal injury). Loss of consciousness is not aprerequisite for mild traumatic brain injury and occurs in less than 5%of mild brain injuries, and head injuries such as diffuse axonal injuryare not detectable in routine CT or MRI scan. High false negativefindings may lead to patients being undiagnosed or misdiagnosed.Unfortunately current imaging methods still lack the resolution andsensitivity to determine functional brain capacity. Rating scales andother neuropsychological and functional examination methods have longbeen used to elucidate these functional questions, but they too arefraught with false negative results and limited specificity.

Problems exist in the collection and management of such large amounts ofdata. The performance of these measurements generate significant amountsof data, both personal in nature the patient, but in need of processingpower to perform proper analysis of the data.

Wearable wireless transmitting physiology sensors and digital recordingand processing of these human physiology measurements have permitted newtechnologies to measure and modify human physiology and to treatdisorders from remote locations around the world.

Therefore, there are needs for insuring the security of such human data.Another need is the importance of mobile access to the testing andtreatment and training data that is housed and managed with smarttechnology that both processes physiology data and allows access toindividual interventions at any suitable location.

BRIEF DESCRIPTION

An object of the disclosed system and method of the present processingtechnology is to utilize a remote processing system that acceptselectrophysiology and related data that is converted into usable reportsand directed instructions to improve human functions. The system andmethod and underlying technology provides for the collection ofphysiology data for remote processing and returned feedback. Moreover,the method and system provides for account management tools relating tothe data and operations associated with the data.

The system and method includes the collection of data using one or moredata collection techniques. These techniques may include the performanceof one or more tests using electrophysiology equipment, including wiredand/or wireless equipment. The testing data is then collected, collated,assembled and may be pre-processed as necessary. The data is thentransmitted to one or more central processing devices for theperformance of processing operations thereon.

In the network-based or cloud-based processing technique, the data isprocessed and managed. Variety of processing operations are performed onthe data to better understand and analyze the data, as well as catalogand centrally store the data.

Therein, the method and system further allows for networked access tothe data, including access by any number of suitable parties. Access mayinclude the patient's doctor reviewing the data for analysis purposesand the prescription of treatment orders.

Therefore, the present method and system allows for the detection andcollection of physiology data, the networked transmission of the data,central processing of the data and the transmission to one or more usersregardless of actual physical location.

In accordance with these and other objects, which will become apparenthereinafter, the disclosed technology will now be described withparticular reference to the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates one embodiment of a device for taking measurements;

FIG. 2 illustrates one embodiment of a block diagram of a method forcarrying measurements;

FIG. 3 illustrates one embodiment of a processing environment for themeasurements and processing described herein;

FIG. 4 illustrates one embodiment of a helmet with electrodes used inthe taking of measurements;

FIG. 5 illustrates one embodiment of a data flow cycle;

FIG. 6 illustrates one embodiment of a data flow diagram illustratingserver-side operations;

FIG. 7 illustrates one embodiment of a data flow diagram for auser-access to the database or network functionality;

FIG. 8 illustrates one embodiment of a data flow diagram for aserver-side payload file processing operation;

FIG. 9 illustrates one embodiment of a data flow diagram of a reportcreator processing operation;

FIG. 10 illustrates another embodiment of a data flow diagram of areport creator processing operation; and

FIG. 11 illustrates one embodiment of multiple server-side applicationsoperative with a plurality of users.

A better understanding of the disclosed technology will be obtained fromthe following detailed description of the preferred embodiments taken inconjunction with the drawings and the attached claims.

DETAILED DESCRIPTION

Various embodiments are described herein, both directly and inherently.However, it is understood that the described embodiments and examplesare not expressly limiting in nature, instead illustrate examples of theadvantageous uses of the innovative teachings herein. In general,statements made in the specification of the present application do notnecessarily limit any of the various claimed inventions and it isrecognized that additional embodiments and variations recognized by oneor more skilled in the art are incorporated herein.

As noted above, the present method and system provides for assembly andcomputational processing of physiology data, specificallyelectrophysiology data. The data is collected and processed in anetworked or server-based processing environment, providing theoffloading of the requisite processing requirements. The data isadditionally managed in the secure network processing environment.

Embodiments of the disclosed technology process provide a combination ofelectroencephalography, electrocardiography, and non-invasivestimulation device usage and associated secure data processing andmanagement. Upon measuring an electrical anomaly in a region of a brainor heart, real time wireless transmission occurs to one or more of ahost local computer, remote computer or central processing unit fromwhich database comparison and processing occurs in order to permitindividual interventions and data analysis, local interventions andreport review.

The present method and system expands the scope of data measurement byincluding active communication to external processing device(s) and/orsystem(s).

The present method and system provides to the measuring locationcomparison databases expanding the comparative ability of the measureddata. In one embodiment, devices of the disclosed technology may utilizevisual, balance, auditory, and other stimuli to test the subject,analyze necessary brain stimulations, and administer stimulation to thebrain. Remote data processing, storage, data mining for further nervoussystem analysis, and merchant account management is embodied in theprocess of engineering computer logic, as described below.

FIG. 1 illustrates a measurement device used to measure the initialdata. A helmet 100 comprises at least one, or a plurality of, electrodes106 (represented as white dots). The helmet may be any receptacle thatholds the electrodes in a position relative to the head of a wearer, oralternatively, electrodes may be taped or otherwise placed on the head.Earphones 102, goggles 104 and/or another display device are used toexhibit stimuli to a user, the stimuli used to vary measurable brainactivity.

The electrodes 106 are electrically connected to one of an electricalstimulation device 150 or electrical measuring device (e.g., a sensor),such as by way of amplifier 152. The same electrode or electrodes may bedisconnected from one such device and connected to another such device,such as by way of changing an electrical pathway (switch) or byphysically disconnecting an electrical wire from one device, andplugging into another. Other devices, not shown, include force platforms(measure postural deviations of person), devices to alter the display onthe goggles 104, and devices to alter the sound through the earphones102, and input devices such as a computer mouse, keyboards, andjoysticks.

Referring now to visual stimuli exhibited on a display device, such asthe goggles 104 of FIG. 1, the visual stimuli produced may be an“immersive environment,” for example a virtual reality 2- or 3-dimensionmoving “room” displayed through a virtual reality headset. The datacollected from the balance plate, heart rate monitor, EEG, and so forth,can be used in conjunction with the visual stimuli forneurophysiological trauma assessment and/or rehabilitation training. Thedata collected from this component, as well as all other components maybe linked with data collected from other components (e.g., EEG, ERP,ECG) for assessment purposes.

The system shown in FIG. 1 may further comprise a vestibular activationtest (VAT) headset permitting a computerized test that monitors thevestibulo-ocular reflex (VOR) during natural motion. A VAT headsetuseful for the systems described herein may produce images and/or recordeye movements. Images displayed in the VAT headset may be generated bycomputer-implemented instructions and transmitted via electricalimpulses to the VAT headset via wireless or direct connection. Eyemovements may be recorded by way of the VAT headset. The VOR is a reflexeye movement that stabilizes images on the retina during head movementby producing an eye movement in the direction opposite to head movement,thus preserving the image on the center of the visual field. As oculartrauma is often concomitant with traumatic brain injury, this componentallows additional assessment of injury.

The measurements of electrophysiological data of a patient may includemeasurements acquired from dry or wet sensors or functional nearinfrared spectroscopy (fNIRs) optical fibers that send light into thescalp at wavelengths in the range of 650-850 nms. The sensors and/orfNIRs may be attached to the non-invasive brain stimulation ormodulation helmet/cap described herein.

Moreover, for clarity purposes, as used herein, a patient may refer toan individual under direct care or supervision of a doctor, but apatient is not so limited and may further include any suitable user orclient wherein measurement data is acquired and analyzed as describedherein. For example, a patient may include non-medically related uses,such as an athlete and the review/analysis of electrophysiological dataof an athlete to analyze possible concussion data. Another example of apatient may be soldiers with the review/analysis of electrophysiologicaldata of the soldiers to analyze data relative to possible traumaticbrain injury or post traumatic stress disorder.

FIG. 2 shows a high level block diagram of a method for acquiring themeasurements. In step 210, non-invasive measurements are made ofelectrical current in the brain of a test subject. This is accomplishedby way of electrodes placed on a test subject, such as in a helmet shownin FIG. 1. In this manner, EEG and ERP signals may be recorded,measured, and analyzed. A single electrode may be used to carry out themeasuring in step 214, or a plurality of electrode pairs may be used instep 212. The position of the electrodes is known, and each electrode ora grouping thereof is placed over a definable region of the brain, theregion defined by a person carrying out embodiments of the disclosedtechnology. The region is defined as a specific brain area of interestfor the recording, as defined by a person carrying out embodiments ofthe disclosed technology and may be a region covered by a singleelectrode pair or as large as half a hemisphere of a brain. Electrodesmay also be grouped into clusters, such as with a single anodesurrounded by three or more cathodes, or a single cathode surrounded bythree or more anodes. Such clusters are electrically connected, suchthat electric current flows non-invasively through the proximal tissuefrom anode(s) to cathode(s), stimulating the brain (stimulating, hereinis defined as passage of electrical current through the brain andincludes increasing or decreasing neuron activity at a site).

While conducting step 210, typically, step 220 is also carried out whichcomprises providing sensory stimulus to a person. This may be done byway of, for example, the goggles shown in FIG. 1 for a visualstimulation 222, auditory stimulation 224, balance stimulation 226,biofeedback measurements 228, or other sensory stimulations known in theart. Definitions and examples of various types of such stimulations areprovided above, before the description of the figures.

Stress tests and peak performance tests may also be performed todetermine, for example, how many times a minute a person is able torespond to a stimulus, or how long a person can hold his/her breath orbalance on a force platform, etc.

Based on the electrical measurements, that is, EEG or ERP measurements,an abnormality in a region of the brain is determined in step 230. Anabnormality may be any of the following: electrical activity which istoo infrequent, too frequent, too low in amplitude, too large inamplitude, an improper pattern of electrical activity,inter-intra-hemispheric connectivity, electrical activity in the wrongportion of the brain for the stimulus given, or the like.

In step 240, based on the located functional abnormality, non-invasivebrain stimulation (such as tDCS) is administered at the region of theAbnormality. In certain cases, the same electrode which was used tomeasure the electrical impulses within the brain is used to administertDCS or other electrical stimulation. In this manner, accuracy of thestimulated region may be assured, as there is no difference in thephysical location on the head where the existing electrical impulse wasmeasured, versus where the new electrical stimulation is administered.The place of administering may be as little as a single anode/cathodepair (or cluster), or may use multiple anode/cathode pairs (orclusters).

Whereby the device of FIG. 1 provides for collection of data, FIG. 3illustrates an embodiment of processing environment providing for theremote database and data analysis method and system operations. In thissystem, the local processing client 302 may be any suitable localprocessing device including but not limited to the collection ofmeasurement data, and/or one or more processing systems for executinginterface operations. For example, in one embodiment the localprocessing client may be a personal computer or a tablet computer havinga browser or application for executing the interface functionalitydescribed herein.

The network 304 may be any suitable network providing communicationthereacross. In one embodiment, the network 302 is an Internetconnection across a public access network, wherein it is recognized thatthe network may include a private and/or secure network, as well asnetwork exchanges via one or more service providers. The network 304operates to facilitate the communication of data between the localprocessing client 302 and the server-side network processing clients306.

The server-side network processing clients 306 may be any suitablenumber of network-processing devices. In one embodiment, the client 306may be a dedicated processing server, wherein in another embodiment, theclient 306 may be any suitable number of distributed computer resourcesfor processing operations as described herein.

As part of the data collection for client 306 processing, FIG. 4 shows aperspective view of a helmet with electrodes used in embodiments of thedisclosed technology. The helmet 400 comprises multiple electrodes, suchas electrodes 442, 444, and 446. As can be seen in the figure, aplurality of electrodes are spaced apart around the interior of a helmetor other piece of headgear and are adapted for both reading electricalactivity from the brain of the wearer and delivering new impulses. Thatis, by way of a single electrode, plurality thereof, cluster ofelectrodes, or plurality of clusters, a joint brain electro-analysis andtranscranial direct current stimulation system (tDCS) comprises aplurality of spaced-apart removable and replaceable electrodes arrangedin an item of headgear. An electroencephalography device (such as anEEG) is wired to each of the electrodes, as is a transcranial directcurrent stimulation device (at the same time or alternating by way of aswitch or plugging/unplugging a cable between the devices).

A cable 450 allows for electrical connectivity between the electrodesand either or both of a tDCS and EEG device. Further, a viser 460 isintegrated with the helmet in embodiments of the disclosed technologyfor optical stimulation (e.g. a video monitor).

Upon measuring an electroencephalography anomaly in a brain region withthe electroencephalography device, transcranial direct currentstimulation is engaged to at least one anode and at least one cathodeelectrode to the brain region where said anomaly was measured.Additional devices such as a force plate, visual stimuli utilizinginteractive games and tests, and the like, may also be utilized.

The data collection techniques and operations, as described in U.S.patent application Ser. No. 13/742,066 and U.S. Pat. Nos. 8,380,316 and8,239,030 are herein incorporated by reference.

The data is collected and thus provided to one or more remote dataprocessing systems. These remote data processing systems may beconnected via a networked connection, including in one embodiment anInternet-based connection. In additional embodiments, the networking maybe via a private or secure network. Wherein, it is noted thatInternet-based connections include the processing of security featureswith the data, to insure the privacy of the data during transmission.

For example, one embodiment may include a data collection computingdevice, such as a personal computer or other type of processing device,operative to receive the electrophysiology data. The processing devicetherein provides for the encryption or inclusion of security features onthe data and the transmission to one or more designated locations. Forexample, one embodiment may include the compression of the data into a“.zip” file.

FIG. 5 illustrates one embodiment of the server-side processing. In thisembodiment, the client side includes the collection of the data and thetransmission to the server. The compressed file is then uncompressed. Acheck determines if the uncompressed file is error-free. If no, a checkdetermines if a there exists a dual copy of the data already on thenetwork.

In one embodiment, the network transmission may include transmissionredundancies including sending or routing data to the server usingmultiple transmission paths or routes. If there is not another copy, thesystem may then seek to improve its operations by copying the bad orcorrupted data to a corrupt data file and sending such information to asystem engineer. Whereupon, that corrupted data may be examined todetermine techniques to improve compression and/or decompression.

If the decompression is proper, one technique is to then count and/ordocument the files within the uncompressed package. In one embodiment, apredetermined file number is set established as a threshold to begin theprocessing of the data files. In this embodiment, the predeterminednumber is 7 such that if greater than 7 files, extract and parse theinfo.data. If less than 7 files and no info.data file, this may indicatebad data on the client side data collection, generation or transmission,therefore the information is again submitted to a quality control groupfor proper refinement of the processing system.

With the inclusion of the info.data file, the server side processingsystem operates to parse and populate database data from the content. Itis recognized by one skilled in the art that the server side or networkside processing may be performing in one or more local or distributedcomputing environment. Similarly, the database and data storage thereonmay be performed in a local data storage device or the database may bedisposed across one or more networks in a distributed environment.

From the extracted and parsed info.data data, the server furtherexecutes one or more software applications for the performance of dataanalysis and computational processing. In one embodiment, this softwareincludes Matlab® applications working in conjunction with the primarydata processing code in code language (e.g., C# and C++) specificallydesigned to process the data in a fully automated manner with flagfeatures that select data analysis results for human review. In thisprocessing, the collected data is then available for execution ofanalysis routines. The Matlab® Software is currently available fromMathWorks, Inc.

The server further provides for the storage of the data and retention ofdata information. In this embodiment, the server creates a postscriptformatted file, such as a PDF file and the database is then updated toinclude storage of this information. In one embodiment the databasefurther includes enhancements to maximize storage, including determiningif the data to be stored is duplicative. If the data is duplicative, asingle data link can be provided, but if the data is not duplicative,then separate access to the data is provided.

The data, including the measurement data and the analyzed data are thenstored in the database, allowing for subsequent user access as describedbelow.

Wherein the present system and method allows for network basedcomputation of the data as described above, the method and systemfurther provides for user access to the network data. The user mayaccess the database via a browser or other type of access device orterminal. In one embodiment, the user may be presented access via apublic network, such as the network, with the proper security orencryption components insuring safe data access and interaction. Inanother embodiment, the computing system may be a dedicated terminal ona private or secure network.

In the data flow diagram of FIG. 6, the client (user) logs into thenetwork. This may be performed using standard logging techniquesrecognized by one skilled in the art. The user may therein be presentedwith a dashboard.

The graphical display of the dashboard may be via an applet or otherlocal or network based executing software. In the dashboard, the usercan execute a software application (widget) to manage account features,the user can execute a search or look-up feature for patients, as wellas other functions. One additional function is the inclusion of a “mostrecent received packages” tab allowing for a user to quickly access andreview recent transactions. Similarly, another tab may be recentlyrequested reports, providing a history of reports the user hasrequested.

In a typical embodiment, the user or client is a doctor or other medicalspecialist having the ability to review, understand and advise a patientbased on the data generated in the reports. As noted above, the datagenerated in the reports relate to the electrophysiology data acquiredfrom patients.

Patient searching functionality can include searches based on patientdetails, scan data and/or past reports. Account management functionsinclude various processing operations to manage the user account,including for example staff management and financial transactionoversight.

Another feature of the interface includes electronic commerce or theability to access commercial features. For example, a user may wish toupgrade electrophysiology equipment, therefore the user can be directedvia the interface. In another example, the user may review the patientdata and appreciate that further refinement of the testing or differenttypes of tests need to be performed to better fine-tune the results,such that medical equipment can be recommended and made available viathe interface.

In one embodiment, the present method and system uses a datanomenclature to better process the data. This exemplary embodimentincludes the following naming standard to shorten, simplify and identifyfour primary characters of a single scan session. Using an example ofCA121P2914S2, the breakdown of the four characteristics are as follows:(CA121P2914S2)

CA=The First two characters of the session identifier represents theclient's company state code.

121=the clients numeric value assigned to the client's company name.Other possible values include 121-1, 212-2, etc. This would occur if theclient has more than one device.

P2914=Patient ID uniquely assigned to a patient at the device level.

S2=Session Number.

In one embodiment, both the Patient ID and the Session Number areassigned to the patient at the time of registration at the device level.Since the devices maintain independent database, both the Patient ID andSession Number are unique to the testing device only. As a result ofthis scenario, a lookup process utilizing data extracted from info.datmay be required to perform a lookup on the master database to validatethere are no other patients that contain the same data based on the dataprior to new record creation.

Another aspect of the invention relates to Payload Delivery, defined asthe compressed and encrypted contents uploaded from a testing device tothe network location. One embodiment of data upload uses known securefile transfer protocols (SFTP), such as the addresssftp.evokeneuroscience.com.

Another aspect is the included Server Side Report Generator Applicationand the requirements associated therewith. Using the included workflowthe requirements of the server side application are as follows:

Item 1: The Application must allow administrators to point to 4 uniqueUNC pathways. (a) Inbound SFTP Watch Folder—Will be used to keep aconstant monitor of the newly received payloads. (b) PermanentRetention—Will be used to store all payloads regardless of successdisposition. (c) Engineering Troubleshooting—Will be the destinationlocation, which will COPY payload source data that error out during thereport generation. And (d) Clinician Review—Will be the destinationlocation, which will COPY payload raw data, generated source data, andgenerated Microsoft Word document(s) for review by the clinician.

Item 2: The application will maintain a constant monitoring of the SFTPWatch Folder mentioned in item 1.a. The monitoring process will berequired to monitor the size grown of payloads as the payloads aredelivered. Any payload that is growing cannot continue to the next stepuntil the payload delivery is complete and file size is static.

Item 3: The application will decompress and decrypt completed payloadsto the permanent retention location outlined in the permanent retentionabove.

Item 4: In addition to the newly decompressed files, the applicationwill MOVE received payload compressed file to the same new permanentdestination as created in item 3. If, the application receives an errorduring the item 3, an additional copy of the payload must be deliveredto the engineering folder outlined in item 1.c. Following the deliveryof the copied payload, an email announcement must be delivered to amonitoring distribution group.

Item 5: Upon completion of item 4 (without incident), the applicationwill count the number of payload contents to insure a minimum of 6files. (a) IF the count is LESS THAN 6 files, perform same errorworkflow outlined in 4.a and 4.a.1. (b) In tandem to the error reportingof 5.a, determine if received payload contents includes an info.datfile. IF info.dat exist, perform item 6.

Item 6: Application will extract and parse data elements from theinfo.dat file from each payload. The following contents will be used topopulate a database stored using a server (e.g., SQL 2008). The fieldsinclude any number of data fields including but not limited to: FieldsInclude; Unique Code; First Name; Last Name; DOB; Test Date; Test Time;Subject Age; Gender; Handedness; Symptoms; and Medications.

The complete system consists of a wireless amplifier equipped to recordartifact free electrical signals from the brain and heart and alsoposition in space using a nine or greater accelerometer. This samedevice is configured to deliver electric current back to the sensorsthat are in contact with the scalp in order to facilitated non-invasivebrain stimulation. Sensors make contact with this skin using either drysensors or electro dermal gel or saline impregnated sensor forconsistent sensor to skin connectivity measured by impedance.

The software provides for automated data collection using scriptsoftware and self-guided instructions. The software sends the resultingdata for algorithm processing either on the CPU or on a dedicated secureserver through an internet connection. This data is processed on the CPUand processed either on the installed database and processing softwareor transmitted to the cloud-based server where processing takes place.

The data analysis is returned in a report format showing physiologygraphics and interpretive results from which the user can makeintervention or diagnostic decisions. Several comparison databases canbe selected from within the software to provide a comparison measure forthe data analysis. Pre-set EEG training protocols (e.g., theta:betaratio training for attention; alpha:theta ratio training for relaxation)are configured for automated home or clinic based training.

Individual baseline data can also be utilized so that the individual'sdata can be compared to an earlier data sample. An example of this is aprofessional athlete having his or her pre-season baseline that is usedfor comparison following a concussion. This is particularly useful forsingle-subject design research of change over time and interventionresults. Group databases such as peak performance or pathologycomparison databases (i.e., Alzheimer's disease sample database) arealso available for selection and data comparison. Intervention optionsinclude real-time noise and artifact removal algorithms that permit EEGand ECG training devoid of movement and other disruptive artifiact orsignal noise. Individual differences from the selected comparisondatabase permits specific or individually derived interventions asnon-invasive brain stimulation (e.g., tDCS/tACS) and brain computerinterface (sLORETA/eLORETA brain computer interface, wavelettime-frequency neurofeedback, event-related potential neurofeedback;Brodman Area selection, neurofeedback, neuro-network brain computerinterface) and peripheral biofeedback such as heart rate variabilitybiofeedback).

The brain computer interface or neurofeedback can include any number ofoperations or techniques, including for example low resolution brainelectromagnetic topography source localization feedback and surfaceelectroencephalography amplitude or phase or coherence feedback.

The user receives report and intervention information from cloud-basedserver interface or from optional embedded software on the CPU for usagewhere internet connectivity is not possible.

The results of the data analysis include a protocol that directs thenon-invasive brain stimulation sensor placements and current parameters.These stimulation protocols can be manually or automatically selected toprovide the user with both brain compute interface training and brainstimulation or brain modulation interventions.

The rapid assessment and re-assessment of the brain and other measuresincluded in the physiology measurement battery allows for rapiddetermination of brain computer interface training location andfrequency protocols and also brain stimulation or modulation usingelectric current. The re-assessment quantifies the difference from thebaseline measure in order to generate a report showing the change madeby either or both brain computer interface and electric current brainmodulation.

The re-assessment then provides an updated intervention protocol.Protocols will vary based on the assessment results such that thedifferent locations on the scalp may be stimulated with differentpolarity at the sensor and with more or less milliamps than one another.Users can manually define scalp location, polarity at the sensor, andmilliamp levels and duration at each location. Users can also selectfrom pre-defined protocols to increase or decrease regional neuronalactivity.

The same data analysis report provides illustration and instruction onthe current flow through the brain tissue in order to further quantifythe cortical excitability relevant to the users clinical or performanceintent. Current flow reporting aid the user with further and morespecific brain modulation targeting protocols using Talairach locationsand Brodmann Areas. The availability of the data analysis and reports onthe web portal allows for telemedicine access and review.

Remote access to data allows for international experts to guide brainassessment and training. The user can generate post-treatment measureswhether the intervention was brain computer interface, targetedmultiple-sensor non-invasive brain stimulation or modulation, or userdefined (e.g., drug trial) interventions. The rapid reporting offunctional measures aid the user to determine the brain function changesfrom the interventions in a rapid and reliable manner.

The sensors permit real time stimulation with electrical current andsimultaneous recording of EEG using signal filters that remove theelectrical stimulation and permit only the EEG and event relatedpotentials to be recorded and processed. This feature permits the userto combine targeted brain stimulation with brain computer interfacetraining using real time artifact correction. Simultaneous neurofeedbackwith stimulation allows for data analysis showing the focal changes ormodulation in the brain from the individual or combined interventionmodalities.

FIG. 7 illustrates a circular data flow diagram representing thecircular operations described herein. The steps are described in greaterdetail herein, wherein FIG. 7 provides a high level overview of oneembodiment of the operation sequences.

Step 700 includes the assessment and re-assessment protocols, such asEEG, ECG, Balance, ERP, etc. Step 702 is the automated data analysis ona CPU or networked server. Step 704 is the report output, which mayinclude output in graphical format with interpretation data. The report704 may further include targeted brain stimulation protocol, functionaltraining protocol with brain computer interface.

Continuing in the cycle of FIG. 7, step 706 is the automated or manualselection of brain stimulation protocol and/or brain computer interfacetraining protocol. Step 708 is an optional real-time assessment duringbrain stimulation or brain computer interface training. Step 710provides automated reporting that reflects changes following brainintervention(s) with report output, which can be available to a userincluding HIPAA-compliant web or network portals.

While the data collection occurs on the client-side, the server sideprocessing allows for enhanced processing operations, including: (1)receiving payload files from client; (2) validating the payload files;and (3) generating one or more report files (e.g. PDF format) for theclient to download or integrate into electronic medical recordssoftware.

To accomplish these goals, the processing is divided into two parts;each part implemented as separate applications. The applications areexecuted on the server-side 306 as noted in FIG. 3.

The first application handles receiving the payload files and validatingtheir contents. The second application will handle the creation of thereport file (e.g. PDF). FIG. 8 illustrates a data flow diagram of theprocess flow of the payload file processing application.

The application monitors the designated folder on the client's ftpserver. When a payload file is uploaded, the application adds that fileto the queue table in the database. The application de-queues a file andwill move the folder to the client's permanent storage folder. Thepayload is unzipped and decrypted, creating a new folder for the payloadwithin the client's permanent storage folder. The contents of thepayload are validated against the business rules specified in MajorApplication Components, Validation section below.

Information from one of the files expected in the payload (info.dat) isparsed and stored in the Patient table in the database. All of the datafiles of the payload are stored in the SessionFile table in thedatabase. If no errors occur during this process, information about thepayload is saved in the SessionQueueState table in the database.

The application uses a notification service to alert specified partieswhen an error occurs during processing or when the payload file violatesa business rule. The notification service sends an email to thespecified email address including a brief description of the issueencountered.

The second application is a report creator. Various embodiments providedata flow operations. FIG. 9 illustrates a first embodiment of a reportgenerator. In this report generation, a successful output is thenotification of the client. Whereas, in the event error(s) occur, theprocess data flow includes notifying a clinician and/or notifyingengineering, which works to assist in process complications.

The first process of the report creator application monitors the reportrequest queue table in the database. A new row in the table indicatesthat a report needs to be created. Using information in the queue table,the report creator executes the report generation application. Thereport generation application returns a code indicating success orfailure.

If the return code indicates success, the client who submitted thepayload from which the report was created is notified that the report isavailable. If the return code indicates an error, the application uses anotification service to alert specified parties when an error occurs.The notification process is the same mentioned in the payload processingabove.

In one embodiment, the data analysis included within the reportgeneration includes multiple processing features. A first feature is theEEG signal data, subject self-report test item data, ECG signal data,accelerometer data is combined and then uploaded from the local CPU tothe network processor using a Watch Folder. As described herein, thedata is acquired using various acquisition techniques applied to thepatient, including running test or other routines on the patient withthe measurement devices. The data may be encrypted for data and patientinformation security.

A second feature of the report generation is that the bundle of data isthen sorted at the server level and each data type is processed for dataintegrity and compared to normative databases, or the same individual'spre-test data comparison, or to a special population comparison database(e.g., Alzheimer Disease, Military Special Operations.). In oneembodiment, the EEG and ECG and accelerometer data are processedinitially with artifact and movement detection and removal software thatincludes independent component analysis (ICA) algorithms. Thepost-cleaned or artifact corrected data is then processed in a manner todisplay graphically the unique characteristics of the electrophysiologydata and based on the database comparison information there is addedinterpretation comments and intervention suggestions that included:medications likely to be effective, supplements likely to be effective,non-invasive brain stimulation protocols, neurofeedback protocols.

A third feature of the report generation includes that the completedreport and all measured and depicted physiology and behavioral data isthen run through algorithms that will flag the report for clinicianreview if particular values are outside normal ranges. If flagged forreview, notice is give the selected clinical and engineering personnelto review and re-upload to the client web portal. If the reported valuesare initially within normal ranges the software will transfer thecompleted report to the client web portal where via username andpassword the client can access the written report in a readable anddownloadable format (e.g., PDF) for printing or upload into electronicmedical records.

In one embodiment, the entire process of initial data transfer to reportavailability is less than one minute and local data analysis can beconfigured to permit faster assessment results in order to facilitate atrain-test-retrain model for clinical or research use.

In one embodiment, the servers-side application uses, in-part, Matlab®components with report generator code to automatically processphysiology data and create data analysis reports.

FIG. 10 illustrates a data flow diagram of a report generation for aclinician resubmission. The second process of the report creatorapplication monitors the clinician resubmission watch folder. A reportfile in this folder indicates that a clinician has corrected a reportfile and wants to submit it to overwrite the original report created forthe session. The clinician creates the updated file (e.g. by saving anupdated Word report file in PDF format) and then moves the updated fileinto the clinician resubmission watch folder.

The report creator application updates the database with informationabout the corrected report file (Session and SessionFile tables). Thereport file is moved to the payload's permanent retention folder andreplaces the previous version of the report file. If this process issuccessful, the client who initially submitted the payload is notifiedthat the report is available.

FIG. 11 illustrates a system diagram of the application componentsdescribed above. FIG. 11 illustrates the three exemplary users,engineering, clinicians and clients. FIG. 11 illustrates theinteractivity for the two server applications described above,applications for data collection and report generation.

A first component is the configuration manager, which providesconfiguration settings for the service side applications to executesuccessfully. It reads configuration settings from the database or aconfiguration file and provides the values to the applications. Thespecifications for the configuration manager component include: (1) readinformation from the Config table in the database using the Data Model;(2) provide value of settings by setting name; and (3) setting valueprovided in the configuration file take priority over that same valuefound in the database.

A second component is a directory watcher. The primary responsibility ofthe directory watcher component is to monitor the designated folder onthe SFTP server for payload files. It moves the payload files to theappropriate permanent retention folder once the payload file upload iscomplete.

The specifications for the directory watcher component includes: (1)configuration parameter to indicate directory to be monitored forincoming payload files; (2) configuration parameter to indicate toplevel directory for permanent client storage; (3) configurationparameter to indicate top level directory for engineering to be used ifthe payload processing causes an error or violates a business rule; (4)verify that payload .zip file upload is complete; (5) verify thatpayload ftp log file is present for a new payload; (6) if aresubmission, payload name will be modified to include a version number;(7) use data model to communicate with database in determining correctversion number; (8) move the payload file(s) to the appropriate clientfolder; (9) use the data model component to insert a row in the payloaddatabase table to indicate a new payload file has been received; (10)use the notification component to alert engineering if there are errorswith any of the above steps; (11) copy the payload to the engineeringdirectory if there are errors with any of the above steps; and (12) useMicrosft.Net FileSystem objects to monitor the inbound directory, movefiles, rename files.

A third component is the Unzip/Decrypt component. The unzip/decryptcomponent will unzip the payload .zip file into the directory in whichthe file resides. If decryption is necessary, this will be done in thesame directory. Specifications for this component include: (1) unzip.zip file in current directory; (2) decrypt file in current directory;(3) use the notification component to alert engineering if there areerrors; (4) copy the payload to the engineering directory if there areerrors; and (5) application uses the DotNetZip library to unzip thepayload files.

Business rules are checked in the validation component. The followingare the current business rules: valid number of files in payload;payload includes info.dat file; and new payload includes ftp log file(only a warning if missing, processing for the payload continues).

The specifications for the validation component includes: (1)configuration parameter to indicate expected number of files in payload;(2) count number of files in payload; (3) check file names to verifythat info.dat is present; (4) check to verify that logfile.txt ispresent if this is a new payload; (5) use the notification component toalert engineering if there are violations of business rules or if thereis an error in any of the above steps; (6) copy the payload to theengineering directory if there are errors with any of the above steps;and (7) use Microsoft.Net FileSystem objects for file checking.

The data model component will communicate get, insert and updatecommands to the database. The other components of the application willsend necessary database requests through this component. Thespecifications for this component include: (1) classes that model thedatabase tables needed for the applications; (2) entity Framework ORMtool will be used to create these classes; and (3) database tables to bemodeled are listed below in the database section

The report creator component checks the database report request queue tosee if any reports need to be created. It calls the report generatorexecutable with the appropriate parameters. The report generator returnsa code to indicate the success or failure of the report generation. Thereport creator also monitors the clinician resubmission watch folder tosee if there any resubmitted reports to process.

The report creation component specification includes: (1) configurationparameter to indicate location of report generator executable; (2)database field to indicate location of template file required for thereport generator; (3) call report generator executable and wait forresponse; (4) notify engineering, clinician or client based on responsecode (e.g. 0=success, notify client report is ready, 1=failure, notifyclinician that review is needed, >1=failure, notify engineering thatreview is needed); (5) if success, check automatic credit redemptionflag to see if client should be charged a credit for the reportautomatically; (6) use data model to update status of payload if reportcreated successfully; (7) use notification component to notifyappropriate party if there are errors; (8) configuration parameter tospecify clinician resubmission watch folder; (9) use data model tocorrectly version session for resubmission; (10) move new PDF report tocorrect retention folder; (11) use data model to update report in thedatabase; and (12) Microsoft.NET file system objects are used to movethe report files.

The notification component's primary responsibility is to sendnotification emails to the appropriate party. Specifications for thiscomponent include: (1) configuration parameter to indicate engineeringemail address; (2) configuration parameter to indicate clinician emailaddress; (3) configuration parameter for SMTP server name or ip address;(4) configuration parameter for SMTP port; (5) need client emailaddress—from database or in constructor; and (6) send email via SMTP

An engineer or clinician can resubmit payload files that result inerrors. The resubmitted payload includes a trailing “-C” or “-E” that ismanually added to the first portion of the file name. The payload fileis then manually copied to the SFTP directory watched by the directorywatcher component. When the file is processed, the file processingapplication is responsible for determining the correct version numberfor the file and renaming it accordingly.

Clinician review could require a new report file be created but wouldnot require resubmission of the entire payload. The new report file canbe resubmitted to the system by manually copying the new file to theclinician resubmission folder watched by the report creator component.The report creator application properly versions the new submission andmoves it to the correct permanent retention folder.

The database can include any suitable data usable for the processingoperations described herein. As part of the server side processing, thedatabase may include the following data types/fields: client;configuration; credit; patient; processing nodes; session data;sessionfile data; sessionoutputstate; sessionReport; andFileHandlingStatus data.

Both server applications are configured to log error messages, warnings,information, and debug messages with several log methods. The messagescan be written to a text file, the server's event log, a database table,or any combination of these methods. Logging of this information isuseful in debugging errors that might occur in the application.Configuration settings will control if logging is turn on and what levelof logging will be triggered.

The applications use NLog for logging. Each application has a separateconfiguration file for NLog settings (NLog.config). NLog is configuredto write to a log file or to the windows event viewer. The log files arelocated in a logs folder within the folder where the application islocated. By default, logging is turned off for each application.

Therefore, the herein described method and system improves uponelectrophysiology measurement and training using a remote database andserver-side analysis and measurement operations. Server side operationsmay be performed in response to executable instructions instructing oneor more processing devices to perform processing operation. Suchexecutable instructions may be stored in one or more computer readablemedia, as recognized by one skilled in the art, such as non-transitorycomputer readable media.

While the disclosed technology has been taught with specific referenceto the above embodiments, a person having ordinary skill in the art willrecognize that changes can be made in form and detail without departingfrom the spirit and the scope of the disclosed technology. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. All changes that come within the meaning and rangeof equivalency of the claims are to be embraced within their scope.Combinations of any of the methods, systems, and devices describedhereinabove are also contemplated and within the scope of the disclosedtechnology.

What is claimed is:
 1. A system for electrophysiological data analysis,the system comprising: a processing device; and a memory device having aplurality of executable instructions stored therein, such that theprocessing device, in response to the executable instructions, isoperative to: retrieve prior measurement data from a comparison datadatabase having the prior measurement data stored therein;electronically analyze electrophysiological data of a patient includingcomparing the electrophysiological data with the prior measurement data,the electrophysiological data including electroencephalography data;update the comparison data database to include the electrophysiologicaldata; generate instructions for a placement of non-invasive brainstimulation sensors on the patient based on the analysis of theelectrophysiological data with the prior measurement data generate atleast one report including the instructions for placement of thenon-invasive brain stimulation sensors; and generate electronic accessto the at least one report, such that the at least one report isavailable to a recipient device for utilization with the patient.
 2. Thesystem of claim 1, wherein the electrophysiological data includes atleast one of: electroencephalography data, event related potential data,electrocardiography data, behavioral measures, and balance data.
 3. Thesystem of claim 1, wherein the electrophysiological data is acquiredfrom the patient using a non-invasive brain stimulation or modulationhelmet/cap having at least one of: dry sensors; wet sensors; andfunctional near infrared spectroscopy optical fibers sending light at awavelength range of 650-850 nm.
 4. The system of claim 1, wherein theprocessing device, in response to further executable instructions, isfurther operative to: receive the electrophysiological data across asecure network connection, wherein the electrophysiological data is in acompressed and secure file format.
 5. The system of claim 1, the atleast one report including intervention options for the patient, whereinthe intervention options include at least one of: non-invasive brainstimulations, brain computer interface or neurofeedback, and peripheralfeedback, wherein the peripheral feedback includes at least one of:balance training and heart rate variability biofeedback.
 6. The systemof claim 5, wherein the brain computer interface or neurofeedbackincludes at least one of: low resolution brain electromagnetictopography source localization feedback and surfaceelectroencephalography amplitude or phase or coherence feedback.
 7. Thesystem of claim 1, wherein the electronic access to the report availableto the recipient device includes storage of the report within a localmemory of the recipient device.
 8. The system of claim 1, wherein theprocessing device is disposed within a networked computing environmentand the report is made available to the recipient device via electronictransmission across a network connection.
 9. The system of claim 1,wherein the processing device is disposed within a local computingenvironment associated with the recipient device.
 10. The system ofclaim 1, wherein the report includes a protocol for non-invasive brainstimulation sensor placement and current parameters.
 11. A method forelectrophysiological report generation, the method comprising:retrieving prior measurement data from a comparison data database havingthe prior measurement data stored therein; electronically analyzingelectrophysiological data of a patient including comparing theelectrophysiological data with the prior measurement data, theelectrophysiological data including electroencephalography data;updating the comparison data database to include theelectrophysiological data; generating instructions for a placement ofnon-invasive brain stimulation sensors on the patient based on theanalysis of the electrophysiological data with the prior measurementdata; generating at least one report including the instructions forplacement of the non-invasive brain stimulation sensors; and generatingelectronic access to the at least one report, such that the at least onereport is available to a recipient for utilization with the patient. 12.The method of claim 11, wherein the electrophysiological data furtherincludes at least one of: event related potential data,electrocardiography data, behavioral measures, and balance data.
 13. Themethod of claim 12, wherein the electrophysiological data is acquiredfrom the patient using a non-invasive brain stimulation or modulationhelmet/cap having at least one of: dry sensors; wet sensors; andfunctional near infrared spectroscopy optical fibers sending light at awavelength range of 650-850 nm.
 14. The method of claim 11 furthercomprising: receiving the electrophysiological data across a securenetwork connection, wherein the electrophysiological data is in acompressed and secure file format.
 15. The method of claim 11, the atleast one report including intervention options for the patient, whereinthe intervention options include at least one of: non-invasive brainstimulations, brain computer interface or neurofeedback, and peripheralfeedback, wherein the peripheral feedback includes at least one of:balance training and heart rate variability biofeedback.
 16. The methodof claim 15, wherein the brain computer interface or neurofeedbackincludes at least one of: low resolution brain electromagnetictopography source localization feedback and surfaceelectroencephalography amplitude or phase or coherence feedback.
 17. Themethod of claim 11, wherein the electronic access to the reportavailable to the recipient includes an electronic transmission across anetwork connection.
 18. The method of claim 11, wherein the reportincludes a protocol for non-invasive brain stimulation sensor placementand current parameters.